Knowledge Commons of Institute of Automation,CAS
Knowledge-aware Attentive Wasserstein Adversarial Dialogue Response Generation | |
Zhang, Yingying1,2![]() ![]() ![]() ![]() | |
发表期刊 | ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY
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ISSN | 2157-6904 |
2020-07-01 | |
卷号 | 11期号:4页码:20 |
摘要 | Natural language generation has become a fundamental task in dialogue systems. RNN-based natural response generation methods encode the dialogue context and decode it into a response. However, they tend to generate dull and simple responses. In this article, we propose a novel framework, called KAWA-DRG (Knowledge-aware Attentive Wasserstein Adversarial Dialogue Response Generation) to model conversation-specific external knowledge and the importance variances of dialogue context in a unified adversarial encoder-decoder learning framework. In KAWA-DRG, a co-attention mechanism attends to important parts within and among context utterances with word-utterance-level attention. Prior knowledge is integrated into the conditional Wasserstein auto-encoder for learning the latent variable space. The posterior and prior distribution of latent variables are generated and trained through adversarial learning. We evaluate our model on Switchboard, DailyDialog, In-Car Assistant, and Ubuntu Dialogue Corpus. Experimental results show that KAWA-DRG outperforms the existing methods. |
关键词 | Dialogue system co-attention adversarial learning external knowledge |
DOI | 10.1145/3384675 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key Research and Development Program of China[2017YFB1002804] ; National Natural Science Foundation of China[61720106006] ; National Natural Science Foundation of China[61572503] ; National Natural Science Foundation of China[61802405] ; National Natural Science Foundation of China[61872424] ; National Natural Science Foundation of China[61702509] ; National Natural Science Foundation of China[61832002] ; National Natural Science Foundation of China[61936005] ; National Natural Science Foundation of China[U1705262] ; Key Research Program of Frontier Sciences, CAS[QYZDJ-SSW-JSC039] ; K.C. Wong Education Foundation |
项目资助者 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; Key Research Program of Frontier Sciences, CAS ; K.C. Wong Education Foundation |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence ; Computer Science, Information Systems |
WOS记录号 | WOS:000583127700002 |
出版者 | ASSOC COMPUTING MACHINERY |
七大方向——子方向分类 | 自然语言处理 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/41806 |
专题 | 多模态人工智能系统全国重点实验室_多媒体计算 |
通讯作者 | Xu, Changsheng |
作者单位 | 1.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, 95 ZhongGuanChun East Rd, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, 95 ZhongGuanChun East Rd, Beijing 100190, Peoples R China 4.Peng Cheng Lab, 95 ZhongGuanChun East Rd, Beijing 100190, Peoples R China |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Zhang, Yingying,Fang, Quan,Qian, Shengsheng,et al. Knowledge-aware Attentive Wasserstein Adversarial Dialogue Response Generation[J]. ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY,2020,11(4):20. |
APA | Zhang, Yingying,Fang, Quan,Qian, Shengsheng,&Xu, Changsheng.(2020).Knowledge-aware Attentive Wasserstein Adversarial Dialogue Response Generation.ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY,11(4),20. |
MLA | Zhang, Yingying,et al."Knowledge-aware Attentive Wasserstein Adversarial Dialogue Response Generation".ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY 11.4(2020):20. |
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